Isolation and identification of the 2,3-BD and γ-PGA co-producing strain
Based on the characteristics of the colonies which were highly mucoid, fifteen strains (CS1‒CS15) were picked up from the agar plates. These strains were transferred into the fermentation medium, and eight strains showed a γ-PGA production ability. Moreover, strain CS13 produced the highest concentration of γ-PGA (9.58 ± 0.28 g/L) (Additional file 1:Table S1). In addition, high concentrations of by-products were found, and one was identified as 2,3-BD during an analysis of residual sugars in the fermentation broth (Additional file 2: Fig. S1). Strain CS11 produced the highest yield of 2,3-BD (15.97 ± 0.51 g/L), and strain CS13 could yield 14.16 ± 0.45 g/L of 2,3-BD. Hence, the idea of the co-production γ-PGA and 2,3-BD arose due to strain CS13.
The 16S rDNA gene sequence of CS13 showed the similarity to B. subtilis subsp. subtilis NCIB 3610 (99.93%), B. subtilis subsp. stercoris D7XPN1 (99.92%), B. tequilensis KCTC 13622 (99.85%), and B. subtilis subsp. inaquosorum KCTC 13429 (99.85%) when blasting the sequence on EzBioCloud. A phylogenetic tree was constructed based on the 16S rDNA sequence and is shown in Fig. 1. CS13 formed a cluster with B. subtilis subsp. stercoris D7XPN1 and was classified as the species B. subtilis. The 16S rDNA gene sequence of B. subtilis CS13 was deposited in Genbank with a gene ID of MG722817. B. subtilis CS13 was deposited at the Korean Collection for Type Cultures with the accession number KCTC 14094 BP.
B. subtilis CS13 is a glutamate-dependent γ-PGA producer, and no γ-PGA was produced in the medium in the absence of L-glutamic acid. The yield of γ-PGA could be controlled by the concentration of exogenous L-glutamic acid thereby controlling the 2,3-BD concentration, which is an interesting phenomenon. Until now, several B. subtilis strains have been isolated from various materials, which can produce either γ-PGA or 2,3-BD, but their co-production has rarely been studied.
Effect of culture parameters for the co-production of 2,3-BD and γ-PGA
Effect of agitation
To investigate the effect of dissolved oxygen on the effect of the γ-PGA and 2,3-BD co-production in flasks, various agitations at 150, 200, and 250 rpm were used for the shakers. The results are shown in Fig. 2a. The biomass showed an increase as the agitation increased up to 250 rpm; however, the highest concentrations of γ-PGA (9.79 ± 0.13 g/L) and 2,3-BD (14.20 ± 0.34 g/L) were obtained at 200 rpm, and there was no significant difference between agitation at 200 and 250 rpm. The low agitation (150 rpm) obviously inhibited the yield of γ-PGA and 2,3-BD.
The high viscosity of the fermentation broth led to a low efficiency of oxygen transfer, and a higher agitation speed improved the oxygen and nutrient supply to the cells. On the other hand, the high viscosity fermentation broth caused the phenomenon of “out-of-phase” operating conditions, significantly reducing the oxygen transfer and mixing intensity [24]; thus, similar results were obtained at 200 and 250 rpm. Previous studies have found that higher dissolved oxygen is beneficial to the production of γ-PGA while lower dissolved oxygen is favorable for 2,3-BD synthesis [14, 25]. To explore the effect of dissolved oxygen and maximize the yield of γ-PGA and 2,3-BD, further research will be carried out in a fermentor. In this study, 200 rpm was used for all subsequent experiments.
Effect of temperature
Figure 2b shows the fermentation results at different temperatures. The biomass decreased from 5.23 ± 0.17 g/L to 3.24 ± 0.09 g/L with increasing temperature from 30 to 45 °C. The high biomass at lower temperatures might be caused by active energy metabolism [15]. The maximum concentration of γ-PGA reached 10.34 ± 0.32 g/L at 45 °C, and the concentration of 2,3-BD was 12.64 ± 0.42 g/L; meanwhile, the highest concentration of 2,3-BD (14.45 ± 0.48 g/L) was obtained at 37 °C with 9.76 ± 0.29 g/L of γ-PGA. The high temperature (45 °C) is favorable for γ-PGA production, but not conducive for 2,3-BD synthesis.
2,3-BD and γ-PGA production are temperature-dependent because of the dependence of the enzyme activity. Perego et al. found that butanediol production increased to the highest value when the temperature was increased to 37 °C and decreased over 37 °C [26]. This phenomenon was consistent with our results. Interestingly, the highest γ-PGA production was obtained at 45 °C. According to the reported literature, each strain has its optimum temperature. B. subtilis (chungkookjang) could produce γ-PGA at 30 °C [27]. Most strains produce γ-PGA at an optimum temperature of 37 °C, such as B. subtilis NX-2, B. subtilis HB-1, and B. subtilis CGMCC 2108 [25, 28, 29]. The optimum temperature for B. subtilis GXA-28 to produce γ-PGA was 45 °C [15], consistent with our result. The high temperature (45 °C) increased the activity of isocitrate dehydrogenase (ICDH) and glutamate dehydrogenase (GDH), which led to an enhanced γ-PGA production. Moreover, the high temperature can reduce the molecular weight of γ-PGA, decrease the viscosity, and improve mass transfer. Considering the production of 2,3-BD, the temperature of 37 °C was chosen as the optimum temperature.
Effect of pH
pH is important in fermentation; thus, the synthesis of γ-PGA and 2,3-BD were investigated at all the tested pH values (5.0‒8.5). The results show that although the biomass was increased with the increase of pH from 5.0‒8.5, the production of γ-PGA and 2,3-BD was significantly changed (Fig. 2c). B. subtilis CS13 showed the highest γ-PGA (9.66 ± 0.31 g/L) and 2,3-BD (14.37 ± 0.45 g/L) production at pH 6.5, followed by 6.0 and 7.0. Nevertheless, γ-PGA and 2,3-BD co-production can adapt to a wide range of pH from 6.0 to 7.5, and more acidity and alkalinity all affect the biosynthesis of γ-PGA and 2,3-BD.
pH influences bacterial metabolism and the formation of products. Zhu et al. found that 2,3-BD was a major by-product at pH 6.5 and 7.3 during γ-PGA fermentation. In contrast, the synthesis of 2,3-BD was limited, and acetoin had a high concentration at pH 5.7 [30]. However, for the B. subtilis CS13 in this study, a low concentration of acetoin (< 0.5 g/L) was detected, and the low pH only decreased the yield of 2,3-BD, which was maybe caused by the high viscosity of broth promoting metabolic flux from acetoin to 2,3-BD. Finally, pH 6.5 was set as the pH for the next experiments.
Effect of carbon sources
The effect of different carbon sources on the γ-PGA and 2,3-BD co-production was investigated by adding sucrose, glucose, fructose, glycerol, maltose, and lactose to the medium at 30 g/L individually, and the results are shown in Fig. 2d. All the tested carbon sources could promote cell growth, but the yield of γ-PGA and 2,3-BD were different. In the case of sucrose and glucose, a high yield of 2,3-BD (14.49 ± 0.47 and 14.33 ± 0.46 g/L) was attained, and the yield of γ-PGA was 9.78 ± 0.32 and 9.65 ± 0.28 g/L, respectively. Lactose was good for cell growth but did not affect the γ-PGA and 2,3-BD co-production. Glycerol was the best carbon source for the γ-PGA production, and 12.24 ± 0.39 g/L of γ-PGA accumulated; but interestingly, glycerol is unfavorable for the synthesis of 2,3-BD, and only 6.93 ± 0.23 g/L of 2,3-BD was produced.
Most of the γ-PGA producers prefer glucose and glycerol as carbon sources. Glucose is utilized mainly to supply the required energy and as a substrate for cell growth during γ-PGA production [31]. Glycerol is used not only as a substrate but also has some functions to enhance the γ-PGA synthesis, such as stimulate polyglutamyl synthetase, improve the permeability of cell membranes, and decrease the broth viscosity [32]. In our results (Fig. 2d), glycerol obviously increased the yield of γ-PGA but reduced the yield of 2,3-BD compared to sucrose or glucose. Actually, glycerol has been used in the production of 2,3-BD by B. amyloliquefaciens, and improved 2,3-BD production through metabolic manipulation [33]. In the utilization of sucrose, B. subtilis NX-2 showed a good advantage to improve the γ-PGA production [16]. Additionally, sucrose was a popular carbon source for production of 2,3-BD [13]. Thus, considering the yield of the 2,3-BD, sucrose as a cheap carbon source was chosen for the γ-PGA and 2,3-BD co-production.
Effect of nitrogen sources
Figure 2e shows the effects of different nitrogen sources on the γ-PGA and 2,3-BD co-production of B. subtilis CS13. All the nitrogen sources could be used by B. subtilis CS13 to synthesis 2,3-BD. In general, the strain preferred to utilize organic nitrogen sources showing improved cell growth and the inorganic nitrogen sources showed an enhanced γ-PGA production. Among the nitrogen sources tested, ammonium citrate yielded the highest γ-PGA (11.68 ± 0.38 g/L) and 2,3-BD (16.32 ± 0.53 g/L) production.
Citrate improved the production of γ-PGA suggesting that citrate enhanced the production of α-ketoglutarate as the precursor for glutamate and γ-PGA in the TCA metabolism [34]. Sodium citrate as a nitrogen source showed a poor result for γ-PGA production (4.99 ± 0.16 g/L), which was caused by the lack of ammonium in the medium. B. subtilis are capable of forming glutamate only in the presence of ammonium and 2-oxoglutarate in vitro [35, 36]. The result also suggests the glutamate used to synthesize γ-PGA comes from an external sucrose and metabolic synthesis. In the present study, B. subtilis CS13 was able to use ammonium sulfate and ammonium chloride for γ-PGA production (Fig. 2e), which is consistent with B. subtilis TAM-4 [37], B. subtilis NX-2 [31] and B. subtilis HSF1410 [36] but different from B. methylotrophicus SK19.001 [38]. Nitrogen sources promote cell growth and γ-PGA synthesis but are strain dependent, which may be caused by differences in metabolism. The results also proved that ammonium citrate was the best for 2,3-BD production, perhaps the high viscosity led to the metabolism necessary for the 2,3-BD synthesis. Previous research also found that ammonium citrate showed significant effects on 2,3-BD production in B. amyloliquefaciens B10-127 [39], but the mechanism is not clear.
Screening of significant nutrients by Plackett-Burman design for co-production
In the present study, B. subtilis CS13 produced the highest yield of γ-PGA (22.37 ± 0.56 g/L) and 2,3-BD (26.23 ± 0.62 g/L) in combinations 6 and 9 (Table 1), and the ANOVA is shown in Table 2. Three variables namely sucrose, L-glutamic acid and ammonium citrate influenced the γ-PGA fermentation process significantly (P < 0.05) and showed a positive coefficient (Table 2a), suggesting that the levels for these variables can be increased to improve the γ-PGA production. In the process of 2,3-BD fermentation, sucrose, L-glutamic acid, ammonium citrate, MgSO4·7H2O, FeCl3·6H2O, and MnCl2·4H2O showed a significant effect. The coefficient of L-glutamic acid, FeCl3·6H2O, and MnCl2·4H2O were negative, and lower concentrations of these chemicals are suggested for future experiments (Table 2b). The coefficient of determination (R2), which equaled 0.9941 and 0.9998 for γ-PGA and 2,3-BD, indicating that 99.41% and 99.98% of the variability in the response could be explained by the model. The high values of the adjusted determination coefficient (R2adj = 0.9787; 0.9993) imply a high significance of the model. The model equations for the γ-PGA and 2,3-BD yield were obtained from the PBD experiments:
where X1, X2, X3, X5, X6, and X7 represent sucrose, L-glutamic acid, ammonium citrate, MgSO4·7H2O, FeCl3·6H2O, and MnCl2·4H2O in the coded level, respectively.
Previous reports have found that L-glutamic acid and citric acid as precursors successfully improve the γ-PGA production [17]; moreover, B. subtilis CS13 belongs to this group. Metallic ions have been shown to have an important role in γ-PGA synthesis. K+ and Ca2+ could increase the activity of enzymes around 2-oxoglutarate in the γ-PGA biosynthesis branch [29, 40]; Fe3+could enhance the expression of γ-PGA synthetase genes (pgs ABC) [41]. However, for B. subtilis CS13, these metallic ions do not affect the γ-PGA production (Table 2b), probably because of the low concentrations of metal ions. L-glutamic acid showed a negative effect only on the margins for 2,3-BD production (P = 0.0378); perhaps, L-glutamic acid enhanced the TCA metabolism pathway, and the real reason needs to be further studied. L-α-acetolactate synthase is a key enzyme from pyruvate to acetoin and 2,3-BD, and the activity of the enzyme is dependent on Mg2+ [42]. Therefore, MgSO4·7H2O showed a positive and significant effect on the 2,3-BD synthesis.
Optimization of the medium composition by response surface methodology
Sucrose, L-glutamic acid, ammonium citrate, and MgSO4·7H2O were used for further optimization with a face-centered central composite design (FCCD) to maximize the γ-PGA and 2,3-BD production. The averages of the maximum values of γ-PGA and 2,3-BD were used as the responses after an 84 h fermentation with 30 experiments in triplicate, and the experimental design is shown in Table 3.
Response surface of the γ-PGA yield
The regression models in the form of ANOVA are given in Table 4a. The “Model-P-value” (< 0.0001) implies the models are significant. The values of the determination coefficient (R2 = 0.9918) indicate a 99.18% variability in the γ-PGA yield. The high values of the adjusted determination coefficient (R2adj = 0.9842) advocate a good term fit for the models. The “Lack of Fit P-value” (0.8992) indicates that the “Lack of Fit” was insignificant relative to the pure error. The “P-value” (< 0.005) showed the significant influence of the coefficients. Among the model terms, sucrose (X1), L-glutamic acid (X2), ammonium citrate (X3), the interaction term of sucrose and L-glutamic acid (X1X2), sucrose and ammonium citrate (X1X3), L-glutamic acid and ammonium citrate (X2X3), squared term of sucrose (X12), L-glutamic acid (X22), ammonium citrate (X32), and MgSO4·7H2O (X52) had a significant influence on the γ-PGA production (Table 4a). The effect of the MgSO4·7H2O and its interaction between the other variables on the γ-PGA yield were not significant. The variables such as sucrose with a positive linear coefficient (2.03) indicate that the production of γ-PGA increased with the increasing concentration of sucrose. Whereas the negative squared coefficient of sucrose (-1.77) suggests the existence of a maximum of as a function of the sucrose concentration, and beyond this point, sucrose had an inhibitory effect (Table 4a). According to ANOVA, the following polynomial quadratic equations were obtained in coded level:
Table 4a
The ANOVA for the γ-PGA production of FCCD
Factors | Mean square | Coefficient estimate | Standard error | F-value | P-value |
Model | 17.97 | 27.24 | 0.12 | 130.22 | < 0.0001 |
X1: Sucrose | 74.38 | 2.03 | 0.088 | 539.10 | < 0.0001 |
X2: L-glutamic acid | 4.38 | 0.49 | 0.088 | 31.75 | < 0.0001 |
X3: Ammonium citric | 7.25 | 0.63 | 0.088 | 52.51 | < 0.0001 |
X5: MgSO4·7H2O | 0.095 | 0.073 | 0.088 | 0.69 | 0.4189 |
X1X2 | 4.77 | -0.55 | 0.093 | 34.60 | < 0.0001 |
X1X3 | 2.31 | -0.38 | 0.093 | 16.75 | 0.0010 |
X1X5 | 1.0 × 10− 4 | -2.5 × 10− 3 | 0.093 | 7.248 × 10− 4 | 0.9789 |
X2X3 | 5.59 | -0.59 | 0.093 | 40.54 | < 0.0001 |
X2X5 | 0.046 | 0.054 | 0.093 | 0.34 | 0.5713 |
X3X5 | 0.12 | 0.088 | 0.093 | 0.89 | 0.3610 |
X12 | 8.10 | -1.77 | 0.23 | 58.67 | < 0.0001 |
X22 | 3.94 | -1.23 | 0.23 | 28.53 | < 0.0001 |
X32 | 6.99 | -1.64 | 0.23 | 50.67 | < 0.0001 |
X52 | 0.64 | -0.50 | 0.23 | 4.65 | 0.0477 |
Lack of Fit | 0.092 | | | 0.40 | 0.8992 |
R2 = 0.9918 | R2 (adj) = 0.9842 | R2 (Pred) = 0.9756 | |
Table 4b
The ANOVA for the 2,3-BD production of FCCD
Factors | Mean square | Coefficient estimate | Standard error | F-value | P-value |
Model | 456.51 | 34.61 | 0.26 | 664.10 | < 0.0001 |
X1: Sucrose | 6309.76 | 18.72 | 0.20 | 9179.15 | < 0.0001 |
X2: L-glutamic acid | 6.43 | -0.60 | 0.20 | 9.36 | 0.0080 |
X3: Ammonium citric | 29.47 | 1.28 | 0.20 | 42.87 | < 0.0001 |
X5: MgSO4·7H2O | 6.93 | 0.62 | 0.20 | 10.08 | 0.0063 |
X1X2 | 0.39 | 0.16 | 0.21 | 0.57 | 0.4609 |
X1X3 | 7.562 × 10− 4 | 6.875 × 10− 3 | 0.21 | 1.100 × 10− 3 | 0.9740 |
X1X5 | 0.8 | 0.18 | 0.21 | 0.73 | 0.4069 |
X2X3 | 0.074 | -0.068 | 0.21 | 0.11 | 0.7469 |
X2X5 | 3.903 × 10− 3 | -0.016 | 0.21 | 5.683 × 10− 3 | 0.9409 |
X3X5 | 4.51 | -0.53 | 0.21 | 6.55 | 0.0218 |
X12 | 29.08 | 3.35 | 0.52 | 42.30 | < 0.0001 |
X22 | 0.047 | 0.13 | 0.52 | 0.069 | 0.7968 |
X32 | 5.15 | -1.41 | 0.52 | 7.49 | 0.0153 |
X52 | 4.24 | -1.28 | 0.52 | 6.18 | 0.0252 |
Lack of Fit | 0.91 | | | 3.68 | 0.0816 |
R2 = 0.9984 | R2 (adj) = 0.9969 | R2 (Pred) = 0.9890 | |
The surface response plots for the optimization of the fermentation conditions of γ-PGA were generated by holding two constants at the central point while keeping another two variables within the experiment range (Fig. 3). Figure 3a-3c shows there were significant interactions of sucrose concentration with other parameters on the γ-PGA yield. The γ-PGA concentration (21‒27 g/L) increased significantly when the sucrose concentration increased from 40‒100 g/L. However, if the sucrose concentration is above 100 g/L, it will decrease the γ-PGA yield, which may be caused by the substrate limitation. A similar effect for ammonium citrate was observed; the ammonium citrate increased to the optimum point increased the γ-PGA production to the maximum level, and a further increase in the ammonium citrate decreased the γ-PGA production (Fig. 3b, 3d, 3f). Figure 3a, 3d, 3e shows that a high γ-PGA yield could be achieved if the concentration of L-glutamic acid is from 30‒50 g/L. The increase of the L-glutamic acid concentration could decrease the γ-PGA yield because L-glutamic acid at too high of a concentration could not be used by strain and substrate limitation occurs. The γ-PGA yield did not change as the MgSO4·7H2O concentration increased due to its insignificant effect (Fig. 3c, 3e, 3f).
Ignoring the effect of MgSO4·7H2O, the maximum value of γ-PGA was predicted by the “Numerical Optimization” tool of the Design Expert 8.0.6 software. The predicted maximum γ-PGA yield was 27.83 g/L, which was obtained with a sucrose of 100.46 g/L, L-glutamic acid of 50.45 g/L, and ammonium citrate of 21.14 g/L.
Response surface of the 2,3-BD yield
The 2,3-BD concentration varied from 13.94 to 56.78 g/L for the 30 experiments shown in Table 3. The model was highly significant as the “Model-P-value” (< 0.0001). The determination coefficient (R2 = 0.9984) and adjusted determination coefficient (R2adj = 0.9969) suggest good fits were achieved by the model (Table 4b). The variables with obvious effect were sucrose (X1), L-glutamic acid (X2), ammonium citrate (X3), MgSO4·7H2O (X5), interaction term of ammonium citrate and MgSO4·7H2O (X3X5), squared term of sucrose (X12), ammonium citrate (X32), and MgSO4·7H2O (X52) (Table 4b). The polynomial quadratic equation in the coded level was given by:
Figure 4a, 4b, 4c deposited the interaction effect of the L-glutamic acid, ammonium citrate, MgSO4·7H2O, and sucrose on 2,3-BD production, respectively. The 2,3-BD concentration increased significantly when the sucrose concentration increased from 40‒120 g/L, different from the other variables, and a high concentration of sucrose did not inhibit the 2,3-BD production within the experiment range. An increase in the ammonium citrate and MgSO4·7H2O increased the 2,3-BD production gradually, and at a higher ammonium citrate and MgSO4·7H2O concentration, the trend was reversed but with a less significant tendency (Fig. 4d). L-glutamic acid inhibited the production of 2,3-BD due to the negative linear coefficient (Table 4b) thus decreased the 2,3-BD concentration with an increase in the L-glutamic acid from 30‒70 g/L (Fig. 4e, 4f). The predicted highest value of 2,3-BD was 57.63 g/L, which was obtained at a sucrose of 120 g/L, L-glutamic acid of 30 g/L, ammonium citrate of 24.51 g/L and MgSO4·7H2O of 3.64 g/L.
Optimization and validation of the medium for the γ-PGA and 2,3-BD co-production
The maximum γ-PGA and 2,3-BD yields were predicted at different concentrations for each variable. L-glutamic acid at a middle level was best for the γ-PGA production whereas it decreased the 2,3-BD concentration. Fortunately, the sucrose concentration at 100.46‒120 g/L and ammonium citrate concentration at 21.14‒24.51 g/L were within the optimum response regions of the γ-PGA and 2,3-BD yield. The optimum medium composition was calculated by a numerical iteration procedure using the Design Expert 8.0.6 software. The optimum conditions for the maximum γ-PGA and 2,3-BD co-production was found to be 119.83 g/L sucrose, 48.85 g/L L-glutamic acid, 21.08 g/L ammonium citrate, and 3.21 g/L MgSO4·7H2O. In this condition, the γ-PGA and 2,3-BD yield predicted by design expert 8.0.6 software were 27.52 and 56.78 g/L, respectively. At the optimum level, the highest yields of γ-PGA and 2,3-BD were 27.79 ± 0.87 and 57.05 ± 1.28 g/L (Fig. 5), which were close to the predicted values.
This design successfully utilizes the metabolic pathways and fermentation conditions of γ-PGA and 2,3-BD. Sucrose was rapidly hydrolyzed to glucose and fructose before 12 h due to the sucrose-utilization systems [1]. Furthermore, the fructose metabolism rate was higher than that of glucose. All of the sugars were exhausted at 84 h, and 57.05 ± 1.28 g/L 2,3-BD was obtained with a productivity of 0.68 g/L/h, and the conversion rate of sucrose to 2, 3-butanediol was 0.475 g 2,3−BD/g sucrose (Fig. 5a). As shown in Fig. 5b, the maximum γ-PGA concentration reached 27.79 ± 0.87 g/L at 24 h of fermentation, and then showed a slow decline, suggesting the γ-PGA depolymerase was activated [43] and “out-of-phase” operating conditions occurred [24]. Additionally, the productivity of γ-PGA was 1.16 g/L/h, which was higher than in some other studies in similar conditions. Furthermore, fed batch operation could be used to achieve a high γ-PGA and 2,3-BD production.
This research not only provides a new strategy to obtain γ-PGA and 2,3-BD simultaneously but also demonstrates the potential for industrial scale. The design utilizes the properties of the products, reduces the production cost and simplifies the steps of industrial separation and purification. At present, the γ-PGA and 2,3-BD are processed mainly according to the properties between the two compounds. Firstly, trichloroacetic acid (TCA) solution is added to the fermentation broth to separate the cells and proteins by centrifugal; second, γ-PGA is obtained through alcohol precipitation and drying and then, the alcohol and 2,3-BD mixture are obtained by aqueous two-phase extraction. The mixture could be used as a fuel or by distillation separation.